# spatstat v1.31-2

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## Spatial Point Pattern analysis, model-fitting, simulation, tests

A package for analysing spatial data, mainly Spatial Point
Patterns, including multitype/marked points and spatial
covariates, in any two-dimensional spatial region. Also
supports three-dimensional point patterns, and space-time point
patterns in any number of dimensions. Contains over 1000
functions for plotting spatial data, exploratory data analysis,
model-fitting, simulation, spatial sampling, model diagnostics,
and formal inference. Data types include point patterns, line
segment patterns, spatial windows, pixel images and
tessellations. Exploratory methods include K-functions,
nearest neighbour distance and empty space statistics, Fry
plots, pair correlation function, kernel smoothed intensity,
relative risk estimation with cross-validated bandwidth
selection, mark correlation functions, segregation indices,
mark dependence diagnostics etc. Point process models can be
fitted to point pattern data using functions ppm, kppm, slrm
similar to glm. Models may include dependence on covariates,
interpoint interaction, cluster formation and dependence on
marks. Fitted models can be simulated automatically. Also
provides facilities for formal inference (such as chi-squared
tests) and model diagnostics (including simulation envelopes,
residuals, residual plots and Q-Q plots).

## Functions in spatstat

Name | Description | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

Concom | The Connected Component Process Model | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

Extract.ppp | Extract or Replace Subset of Point Pattern | |

Gest | Nearest Neighbour Distance Function G | |

as.function.fv | Convert Function Value Table to Function | |

Pairwise | Generic Pairwise Interaction model | |

Extract.splitppp | Extract or Replace Sub-Patterns | |

Hybrid | Hybrid Interaction Point Process Model | |

Extract.layered | Extract Subset of a Layered Object | |

Poisson | Poisson Point Process Model | |

bw.frac | Bandwidth Selection Based on Window Geometry | |

OrdThresh | Ord's Interaction model | |

Kscaled | Locally Scaled K-function | |

Kmodel | K function of a model | |

Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |

Linhom | L-function | |

Kest | K-function | |

chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |

Iest | Estimate the I-function | |

addvar | Added Variable Plot for Point Process Model | |

Jinhom | Inhomogeneous J-function | |

LambertW | Lambert's W Function | |

F3est | Empty Space Function of a Three-Dimensional Point Pattern | |

Lest | L-function | |

areaLoss | Difference of Disc Areas | |

Kest.fft | K-function using FFT | |

Extract.tess | Extract or Replace Subset of Tessellation | |

Replace.im | Reset Values in Subset of Image | |

MultiStrauss | The Multitype Strauss Point Process Model | |

Jdot | Multitype J Function (i-to-any) | |

bermantest | Berman's Tests for Point Process Model | |

G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |

DiggleGratton | Diggle-Gratton model | |

Fiksel | The Fiksel Interaction | |

Jest | Estimate the J-function | |

Fest | Estimate the empty space function F | |

as.hyperframe | Convert Data to Hyperframe | |

Extract.owin | Extract Subset of Window | |

blur | Apply Gaussian Blur to a Pixel Image | |

Extract.linnet | Extract Subset of Linear Network | |

AreaInter | The Area Interaction Point Process Model | |

Kcom | Model Compensator of K Function | |

Jmulti | Marked J Function | |

bramblecanes | Hutchings' Bramble Canes data | |

convexhull.xy | Convex Hull of Points | |

Extract.ppx | Extract Subset of Multidimensional Point Pattern | |

affine.psp | Apply Affine Transformation To Line Segment Pattern | |

MultiHard | The Multitype Hard Core Point Process Model | |

affine.owin | Apply Affine Transformation To Window | |

Strauss | The Strauss Point Process Model | |

Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |

Kres | Residual K Function | |

DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |

as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |

bounding.box.xy | Convex Hull of Points | |

SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |

as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |

Extract.listof | Extract or Replace Subset of a List of Things | |

adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |

clmfires | Castilla-La Mancha Forest Fires | |

as.box3 | Convert Data to Three-Dimensional Box | |

coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |

border | Border Region of a Window | |

Finhom | Inhomogeneous Empty Space Function | |

Gfox | Foxall's Distance Functions | |

as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |

Hest | Spherical Contact Distribution Function | |

as.owin | Convert Data To Class owin | |

Extract.fasp | Extract Subset of Function Array | |

BadGey | Hybrid Geyer Point Process Model | |

Extract.lpp | Extract Subset of Point Pattern on Linear Network | |

Extract.fv | Extract Subset of Function Values | |

Extract.msr | Extract Subset of Signed or Vector Measure | |

circumradius | Circumradius and Diameter of a Linear Network | |

copper | Berman-Huntington points and lines data | |

colourmap | Colour Lookup Tables | |

Extract.im | Extract Subset of Image | |

amacrine | Hughes' Amacrine Cell Data | |

Kdot | Multitype K Function (i-to-any) | |

as.im | Convert to Pixel Image | |

K3est | K-function of a Three-Dimensional Point Pattern | |

cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |

PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |

coef.ppm | Coefficients of Fitted Point Process Model | |

Hardcore | The Hard Core Point Process Model | |

Extract.quad | Subset of Quadrature Scheme | |

as.interact | Extract Interaction Structure | |

complement.owin | Take Complement of a Window | |

Geyer | Geyer's Saturation Point Process Model | |

Ord | Generic Ord Interaction model | |

Kmeasure | Reduced Second Moment Measure | |

distcdf | Distribution Function of Interpoint Distance | |

Jcross | Multitype J Function (i-to-j) | |

angles.psp | Orientation Angles of Line Segments | |

bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |

Gcom | Model Compensator of Nearest Neighbour Function | |

Gres | Residual G Function | |

crossdist.ppp | Pairwise distances between two different point patterns | |

Kinhom | Inhomogeneous K-function | |

Kmulti | Marked K-Function | |

LennardJones | The Lennard-Jones Potential | |

affine.lpp | Apply Geometrical Transformations to Point Pattern on a Linear Network | |

bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

Kcross | Multitype K Function (Cross-type) | |

Ldot | Multitype L-function (i-to-any) | |

density.psp | Kernel Smoothing of Line Segment Pattern | |

as.linim | Convert to Pixel Image on Linear Network | |

ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |

incircle | Find Largest Circle Inside Window | |

betacells | Beta Ganglion Cells in Cat Retina | |

dfbetas.ppm | Parameter influence measure | |

fv.object | Function Value Table | |

as.data.frame.im | Convert Pixel Image to Data Frame | |

Emark | Diagnostics for random marking | |

clarkevans | Clark and Evans Aggregation Index | |

crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |

cut.ppp | Classify Points in a Point Pattern | |

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

ants | Harkness-Isham ants' nests data | |

by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |

Gmulti | Marked Nearest Neighbour Distance Function | |

by.im | Apply Function to Image Broken Down by Factor | |

MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |

Lcross | Multitype L-function (cross-type) | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

affine.ppp | Apply Affine Transformation To Point Pattern | |

hybrid.family | Hybrid Interaction Family | |

identify.psp | Identify Segments in a Line Segment Pattern | |

eem | Exponential Energy Marks | |

dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |

Triplets | The Triplet Point Process Model | |

im.object | Class of Images | |

as.rectangle | Window Frame | |

delaunay | Delaunay Triangulation of Point Pattern | |

cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |

connected | Connected components | |

as.tess | Convert Data To Tessellation | |

fv | Create a Function Value Table | |

eval.fv | Evaluate Expression Involving Functions | |

as.ppp | Convert Data To Class ppp | |

bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |

bei | Tropical rain forest trees | |

im | Create a Pixel Image Object | |

is.multitype | Test whether Object is Multitype | |

cut.im | Convert Pixel Image from Numeric to Factor | |

density.ppp | Kernel Smoothed Intensity of Point Pattern | |

edges2triangles | List Triangles in a Graph | |

StraussHard | The Strauss / Hard Core Point Process Model | |

hyperframe | Hyper Data Frame | |

affine | Apply Affine Transformation | |

data.ppm | Extract Original Data from a Fitted Point Process Model | |

fitted.ppm | Fitted Conditional Intensity for Point Process Model | |

Saturated | Saturated Pairwise Interaction model | |

discpartarea | Area of Part of Disc | |

linnet | Create a Linear Network | |

levelset | Level Set of a Pixel Image | |

dilation | Morphological Dilation | |

Softcore | The Soft Core Point Process Model | |

distmap.ppp | Distance Map of Point Pattern | |

allstats | Calculate four standard summary functions of a point pattern. | |

idw | Inverse-distance weighted smoothing of observations at irregular points | |

affine.im | Apply Affine Transformation To Pixel Image | |

boxx | Multi-Dimensional Box | |

clickjoin | Interactively join vertices on a plot | |

methods.units | Methods for Units | |

diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |

areaGain | Difference of Disc Areas | |

cells | Biological Cells Point Pattern | |

alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |

crossdist.default | Pairwise distances between two different sets of points | |

closing | Morphological Closing | |

bdist.pixels | Distance to Boundary of Window | |

envelope.envelope | Recompute Envelopes | |

envelope.lpp | Envelope for Point Patterns on Linear Network | |

infline | Infinite Straight Lines | |

endpoints.psp | Endpoints of Line Segment Pattern | |

ippm | Optimise Irregular Trend Parameters in Point Process Model | |

distmap | Distance Map | |

is.marked.ppm | Test Whether A Point Process Model is Marked | |

lansing | Lansing Woods Point Pattern | |

interp.im | Interpolate a Pixel Image | |

as.ppm | Extract Fitted Point Process Model | |

as.matrix.owin | Convert Pixel Image to Matrix | |

as.matrix.im | Convert Pixel Image to Matrix or Array | |

applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |

linearK | Linear K Function | |

as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |

clickppp | Interactively Add Points | |

chicago | Chicago Street Crime Data | |

is.multitype.ppm | Test Whether A Point Process Model is Multitype | |

nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |

expand.owin | Apply Expansion Rule | |

lurking | Lurking variable plot | |

clusterset | Allard-Fraley Estimator of Cluster Feature | |

as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |

Tstat | Third order summary statistic | |

connected.ppp | Connected components of a point pattern | |

bind.fv | Combine Function Value Tables | |

clarkevans.test | Clark and Evans Test | |

duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |

linearpcf | Linear Pair Correlation Function | |

anemones | Beadlet Anemones Data | |

affine.linnet | Apply Geometrical Transformations to a Linear Network | |

default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |

contour.im | Contour plot of pixel image | |

diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |

inforder.family | Infinite Order Interaction Family | |

dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |

nearestsegment | Find Line Segment Nearest to Each Point | |

methods.pp3 | Methods for three-dimensional point patterns | |

cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |

pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |

envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |

collapse.fv | Collapse Several Function Tables into One | |

as.polygonal | Convert a Window to a Polygonal Window | |

discretise | Safely Convert Point Pattern Window to Binary Mask | |

crossing.psp | Crossing Points of Two Line Segment Patterns | |

heather | Diggle's Heather Data | |

colourtools | Convert and Compare Colours in Different Formats | |

marks | Marks of a Point Pattern | |

lut | Lookup Tables | |

coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |

is.marked | Test Whether Marks Are Present | |

plot.fasp | Plot a Function Array | |

anova.ppm | ANOVA for Fitted Point Process Models | |

bounding.box | Bounding Box of a Window or Point Pattern | |

model.matrix.slrm | Extract Design Matrix from Spatial Logistic Regression Model | |

chorley | Chorley-Ribble Cancer Data | |

plot.layered | Layered Plot | |

convexhull | Convex Hull | |

centroid.owin | Centroid of a window | |

bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |

methods.linnet | Methods for Linear Networks | |

owin | Create a Window | |

integral.im | Integral of a Pixel Image | |

as.mask | Pixel Image Approximation of a Window | |

km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

box3 | Three-Dimensional Box | |

distfun | Distance Map as a Function | |

hamster | Aherne's hamster tumour data | |

istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |

finpines | Pine saplings in Finland. | |

diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |

effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |

bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |

bronzefilter | Bronze gradient filter data | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

pcfinhom | Inhomogeneous Pair Correlation Function | |

as.psp | Convert Data To Class psp | |

envelope | Simulation Envelopes of Summary Function | |

lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |

crossdist.lpp | Pairwise distances between two point patterns on a linear network | |

linearKinhom | Inhomogeneous Linear K Function | |

is.owin | Test Whether An Object Is A Window | |

diameter | Diameter of an Object | |

letterR | Window in Shape of Letter R | |

diameter.owin | Diameter of a Window | |

lengths.psp | Lengths of Line Segments | |

leverage.ppm | Leverage Measure for Spatial Point Process Model | |

mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |

localpcf | Local pair correlation function | |

append.psp | Combine Two Line Segment Patterns | |

model.matrix.ppm | Extract Design Matrix from Point Process Model | |

dclf.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests | |

erosion | Morphological Erosion | |

methods.funxy | Methods for Spatial Functions | |

compatible.fasp | Test Whether Function Arrays Are Compatible | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

demopat | Artificial Data Point Pattern | |

nndist | Nearest neighbour distances | |

markcorr | Mark Correlation Function | |

lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

distmap.psp | Distance Map of Line Segment Pattern | |

mucosa | Cells in Gastric Mucosa | |

delaunay.distance | Distance on Delaunay Triangulation | |

rSSI | Simulate Simple Sequential Inhibition | |

intensity.ppp | Empirical Intensity of Point Pattern | |

pairdist | Pairwise distances | |

iplot | Point and Click Interface for Displaying Spatial Data | |

is.ppp | Test Whether An Object Is A Point Pattern | |

pairdist.ppp | Pairwise distances | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

miplot | Morishita Index Plot | |

mincontrast | Method of Minimum Contrast | |

identify.ppp | Identify Points in a Point Pattern | |

compatible.fv | Test Whether Function Objects Are Compatible | |

intensity.lpp | Empirical Intensity of Point Pattern on Linear Network | |

concatxy | Concatenate x,y Coordinate Vectors | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

is.im | Test Whether An Object Is A Pixel Image | |

methods.layered | Methods for Layered Objects | |

default.expand | Default Expansion Rule for Simulation of Model | |

rPoissonCluster | Simulate Poisson Cluster Process | |

nncross | Nearest Neighbours Between Two Patterns | |

rescale.im | Convert Pixel Image to Another Unit of Length | |

paracou | Kimboto trees at Paracou, French Guiana | |

redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |

distmap.owin | Distance Map of Window | |

is.lpp | Test Whether An Object Is A Point Pattern on a Linear Network | |

clickpoly | Interactively Define a Polygon | |

default.dummy | Generate a Default Pattern of Dummy Points | |

kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |

sharpen | Data Sharpening of Point Pattern | |

methods.box3 | Methods for Three-Dimensional Box | |

funxy | Spatial Function Class | |

gpc2owin | Convert Polygonal Region into Different Format | |

hist.im | Histogram of Pixel Values in an Image | |

is.ppm | Test Whether An Object Is A Fitted Point Process Model | |

timed | Record the Computation Time | |

kstest.ppm | Kolmogorov-Smirnov Test for Point Pattern or Point Process Model | |

pairsat.family | Saturated Pairwise Interaction Point Process Family | |

markcorrint | Mark Correlation Integral | |

pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |

latest.news | Print News About Latest Version of Package | |

methods.boxx | Methods for Multi-Dimensional Box | |

nnclean | Nearest Neighbour Clutter Removal | |

is.hybrid | Test Whether Object is a Hybrid | |

is.multitype.ppp | Test Whether A Point Pattern is Multitype | |

matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |

pool.quadrattest | Pool Several Quadrat Tests | |

fasp.object | Function Arrays for Spatial Patterns | |

density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |

rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |

rshift.splitppp | Randomly Shift a List of Point Patterns | |

rpoislpp | Poisson Point Process on a Linear Network | |

fryplot | Fry Plot of Point Pattern | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

gridcentres | Rectangular grid of points | |

is.rectangle | Determine Type of Window | |

formula.ppm | Model Formulae for Gibbs Point Process Models | |

lineardisc | Compute Disc of Given Radius in Linear Network | |

psp | Create a Line Segment Pattern | |

bdist.tiles | Distance to Boundary of Window | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |

pairdist.default | Pairwise distances | |

clip.infline | Intersect Infinite Straight Lines with a Window | |

compatible | Test Whether Objects Are Compatible | |

trim.rectangle | Cut margins from rectangle | |

is.stationary | Recognise Stationary and Poisson Point Process Models | |

exactMPLEstrauss | Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process | |

matchingdist | Distance for a Point Pattern Matching | |

plot.bermantest | Plot Result of Berman Test | |

methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates | |

harmonic | Basis for Harmonic Functions | |

osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |

layered | Create List of Plotting Layers | |

nndist.psp | Nearest neighbour distances between line segments | |

plot.ppp | plot a Spatial Point Pattern | |

commonGrid | Determine A Common Spatial Domain And Pixel Resolution | |

quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |

is.convex | Test Whether a Window is Convex | |

plot.ppm | plot a Fitted Point Process Model | |

pixellate.ppp | Convert Point Pattern to Pixel Image | |

rMosaicSet | Mosaic Random Set | |

crossdist.psp | Pairwise distances between two different line segment patterns | |

markvario | Mark Variogram | |

print.owin | Print Brief Details of a Spatial Window | |

pcf.fasp | Pair Correlation Function obtained from array of K functions | |

eval.im | Evaluate Expression Involving Pixel Images | |

dilated.areas | Areas of Morphological Dilations | |

pairs.im | Scatterplot Matrix for Pixel Images | |

imcov | Spatial Covariance of a Pixel Image | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

pppmatching.object | Class of Point Matchings | |

pcfcross | Multitype pair correlation function (cross-type) | |

pcfdot | Multitype pair correlation function (i-to-any) | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

owin.object | Class owin | |

pcf | Pair Correlation Function | |

japanesepines | Japanese Pines Point Pattern | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

periodify | Make Periodic Copies of a Spatial Pattern | |

rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |

opening | Morphological Opening | |

perimeter | Perimeter Length of Window | |

gordon | People in Gordon Square | |

rLGCP | Simulate Log-Gaussian Cox Process | |

flu | Influenza Virus Proteins | |

predict.ppm | Prediction from a Fitted Point Process Model | |

methods.slrm | Methods for Spatial Logistic Regression Models | |

pixellate.psp | Convert Line Segment Pattern to Pixel Image | |

kppm | Fit Cluster or Cox Point Process Model | |

formula.fv | Extract or Change the Plot Formula for a Function Value Table | |

influence.ppm | Influence Measure for Spatial Point Process Model | |

murchison | Murchison gold deposits | |

hyytiala | Scots pines and other trees at Hyytiala | |

update.rmhcontrol | Update Control Parameters of Metropolis-Hastings Algorithm | |

qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |

triplet.family | Triplet Interaction Family | |

longleaf | Longleaf Pines Point Pattern | |

model.images | Compute Images of Constructed Covariates | |

pixellate | Convert Spatial Object to Pixel Image | |

rescale | Convert dataset to another unit of length | |

plot.leverage.ppm | Plot Leverage Function | |

methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |

nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |

rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |

msr | Signed or Vector-Valued Measure | |

pool.rat | Pool Data from Several Ratio Objects | |

waka | Trees in Waka national park | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

linim | Create Pixel Image on Linear Network | |

disc | Circular Window | |

ord.family | Ord Interaction Process Family | |

licence.polygons | Restricted Licence Conditions for Polygon Calculations | |

plot.im | Plot a Pixel Image | |

rsyst | Simulate systematic random point pattern | |

urkiola | Urkiola Woods Point Pattern | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

rhohat | Smoothing Estimate of Covariate Transformation | |

pool.envelope | Pool Data from Several Envelopes | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

plot.psp | plot a Spatial Line Segment Pattern | |

rMatClust | Simulate Matern Cluster Process | |

marks.psp | Marks of a Line Segment Pattern | |

intensity.ppm | Intensity of Fitted Point Process Model | |

methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |

plot.linim | Plot Pixel Image on Linear Network | |

model.frame.ppm | Extract the Variables in a Point Process Model | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |

rStrauss | Perfect Simulation of the Strauss Process | |

marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |

rmhexpand | Specify Simulation Window or Expansion Rule | |

ppm | Fit Point Process Model to Data | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

intensity | Intensity of a Dataset or a Model | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

lppm | Fit Point Process Model to Point Pattern on Linear Network | |

plot.colourmap | Plot a Colour Map | |

methods.lpp | Methods for Point Patterns on a Linear Network | |

relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |

plot.quad | plot a Spatial Quadrature Scheme | |

pp3 | Three Dimensional Point Pattern | |

pixellate.owin | Convert Window to Pixel Image | |

simplify.owin | Approximate a Polygon by a Simpler Polygon | |

rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |

psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |

rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |

rpoisline | Generate Poisson Random Line Process | |

localK | Neighbourhood density function | |

fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |

split.ppp | Divide Point Pattern into Sub-patterns | |

logLik.ppm | Log Likelihood and AIC for Point Process Model | |

residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |

pppmatching | Create a Point Matching | |

runiflpp | Uniform Random Points on a Linear Network | |

summary.ppm | Summarizing a Fitted Point Process Model | |

print.im | Print Brief Details of an Image | |

ppp | Create a Point Pattern | |

methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |

eroded.areas | Areas of Morphological Erosions | |

is.marked.ppp | Test Whether A Point Pattern is Marked | |

lpp | Create Point Pattern on Linear Network | |

plot.tess | Plot a tessellation | |

pool.fasp | Pool Data from Several Function Arrays | |

pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |

profilepl | Profile Maximum Pseudolikelihood | |

thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |

plot.kppm | Plot a fitted cluster point process | |

inside.owin | Test Whether Points Are Inside A Window | |

npfun | Dummy Function Returns Number of Points | |

ppx | Multidimensional Space-Time Point Pattern | |

rstrat | Simulate Stratified Random Point Pattern | |

contour.listof | Plot a List of Things | |

markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |

pool | Pool Data | |

rotate.owin | Rotate a Window | |

nsegments | Number of Line Segments in a Line Segment Pattern | |

rescale.owin | Convert Window to Another Unit of Length | |

midpoints.psp | Midpoints of Line Segment Pattern | |

rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |

layerplotargs | Extract or Replace the Plot Arguments of a Layered Object | |

rHardcore | Perfect Simulation of the Hardcore Process | |

summary.psp | Summary of a Line Segment Pattern Dataset | |

project2segment | Move Point To Nearest Line | |

runifpointOnLines | Generate N Uniform Random Points On Line Segments | |

nnwhich | Nearest neighbour | |

rMaternII | Simulate Matern Model II | |

quadrat.test | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |

reduced.sample | Reduced Sample Estimator using Histogram Data | |

reflect | Reflect In Origin | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

rThomas | Simulate Thomas Process | |

rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |

plot.envelope | Plot a Simulation Envelope | |

superimpose | Superimpose Several Geometric Patterns | |

shift.im | Apply Vector Translation To Pixel Image | |

predict.lppm | Predict Point Process Model on Linear Network | |

ppp.object | Class of Point Patterns | |

plot.kstest | Plot a Spatial Kolmogorov-Smirnov Test | |

plot.hyperframe | Plot Entries in a Hyperframe | |

rStraussHard | Perfect Simulation of the Strauss-Hardcore Process | |

pairdist.psp | Pairwise distances between line segments | |

plot.msr | Plot a Signed or Vector-Valued Measure | |

print.ppm | Print a Fitted Point Process Model | |

runifpoint | Generate N Uniform Random Points | |

predict.kppm | Prediction from a Fitted Cluster Point Process Model | |

spatstat-deprecated | Deprecated spatstat functions | |

pcf.fv | Pair Correlation Function obtained from K Function | |

nndist.pp3 | Nearest neighbour distances in three dimensions | |

model.depends | Identify Covariates Involved in each Model Term | |

simdat | Simulated Point Pattern | |

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

suffstat | Sufficient Statistic of Point Process Model | |

rat | Ratio object | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

rotate.ppp | Rotate a Point Pattern | |

nztrees | New Zealand Trees Point Pattern | |

psp.object | Class of Line Segment Patterns | |

print.psp | Print Brief Details of a Line Segment Pattern Dataset | |

rescue.rectangle | Convert Window Back To Rectangle | |

scalardilate | Apply Scalar Dilation | |

swedishpines | Swedish Pines Point Pattern | |

plot.plotppm | Plot a plotppm Object Created by plot.ppm | |

plot.fv | Plot Function Values | |

nnfun | Nearest Neighbour Map as a Function | |

spatstat.options | Internal Options in Spatstat Package | |

shapley | Galaxies in the Shapley Supercluster | |

plot.pp3 | Plot a three-dimensional point pattern | |

with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |

tess | Create a Tessellation | |

setcov | Set Covariance of a Window | |

summary.owin | Summary of a Spatial Window | |

smooth.fv | Apply Smoothing to Function Values | |

update.kppm | Update a Fitted Cluster Point Process Model | |

scan.test | Spatial Scan Test | |

spokes | Spokes pattern of dummy points | |

simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |

zapsmall.im | Rounding of Pixel Values | |

rNeymanScott | Simulate Neyman-Scott Process | |

ripras | Estimate window from points alone | |

persp.im | Perspective Plot of Pixel Image | |

pppdist | Distance Between Two Point Patterns | |

rotate | Rotate | |

progressreport | Print Progress Reports | |

slrm | Spatial Logistic Regression | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

summary.quad | Summarizing a Quadrature Scheme | |

shift.ppp | Apply Vector Translation To Point Pattern | |

rshift.ppp | Randomly Shift a Point Pattern | |

pcf.ppp | Pair Correlation Function of Point Pattern | |

rthin | Random Thinning | |

print.ppp | Print Brief Details of a Point Pattern Dataset | |

plot.splitppp | Plot a List of Point Patterns | |

parres | Partial Residuals for Point Process Model | |

rounding | Detect Numerical Rounding | |

vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |

vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |

rMosaicField | Mosaic Random Field | |

rpoislinetess | Poisson Line Tessellation | |

project.ppm | Force Point Process Model to be Valid | |

markconnect | Mark Connection Function | |

is.empty | Test Whether An Object Is Empty | |

rescale.ppp | Convert Point Pattern to Another Unit of Length | |

whist | Weighted Histogram | |

spatstat-package | The Spatstat Package | |

vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |

rotate.im | Rotate a Pixel Image | |

smooth.ppp | Spatial smoothing of observations at irregular points | |

rlinegrid | Generate grid of parallel lines with random displacement | |

runifpointx | Generate N Uniform Random Points in Any Dimensions | |

plot.influence.ppm | Plot Influence Measure | |

transect.im | Pixel Values Along a Transect | |

rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |

split.ppx | Divide Multidimensional Point Pattern into Sub-patterns | |

sidelengths.owin | Side Lengths of Enclosing Rectangle of a Window | |

rjitter | Random Perturbation of a Point Pattern | |

rshift.psp | Randomly Shift a Line Segment Pattern | |

runifdisc | Generate N Uniform Random Points in a Disc | |

plot.owin | Plot a Spatial Window | |

unmark | Remove Marks | |

print.quad | Print a Quadrature Scheme | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

simulate.kppm | Simulate a Fitted Cluster Point Process Model | |

rcell | Simulate Baddeley-Silverman Cell Process | |

plot.listof | Plot a List of Things | |

quadratcount | Quadrat counting for a point pattern | |

raster.x | Cartesian Coordinates for a Pixel Raster | |

unnormdensity | Weighted kernel smoother | |

rlabel | Random Re-Labelling of Point Pattern | |

rpoispp | Generate Poisson Point Pattern | |

plot.linnet | Plot a linear network | |

rotate.psp | Rotate a Line Segment Pattern | |

rmh.ppm | Simulate from a Fitted Point Process Model | |

with.fv | Evaluate an Expression in a Function Table | |

update.ppm | Update a Fitted Point Process Model | |

rmpoint | Generate N Random Multitype Points | |

sumouter | Compute Quadratic Forms | |

rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |

psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |

ppm.object | Class of Fitted Point Process Models | |

quantile.im | Sample Quantiles of Pixel Image | |

summary.splitppp | Summary of a Split Point Pattern | |

square | Square Window | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

rMaternI | Simulate Matern Model I | |

which.max.im | Identify Pixelwise Maximum of Several Pixel Images | |

quadscheme | Generate a Quadrature Scheme from a Point Pattern | |

unique.ppp | Extract Unique Points from a Spatial Point Pattern | |

predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |

shift.psp | Apply Vector Translation To Line Segment Pattern | |

varblock | Estimate Variance of Summary Statistic by Subdivision | |

smooth.msr | Smooth a Signed or Vector-Valued Measure | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

spruces | Spruces Point Pattern | |

spatstat-internal | Internal spatstat functions | |

quadrats | Divide Region into Quadrats | |

shift | Apply Vector Translation | |

vcov.slrm | Variance-Covariance Matrix for a Fitted Spatial Logistic Regression | |

unitname | Name for Unit of Length | |

summary.listof | Summary of a List of Things | |

rcellnumber | Generate Random Numbers of Points for Cell Process | |

shift.owin | Apply Vector Translation To Window | |

redwood | California Redwoods Point Pattern (Ripley's Subset) | |

rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |

sessionLibs | Print Names and Version Numbers of Libraries Loaded | |

rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |

rshift | Random Shift | |

split.im | Divide Image Into Sub-images | |

runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |

selfcrossing.psp | Crossing Points in a Line Segment Pattern | |

simplenet | Simple Example of Linear Network | |

union.quad | Union of Data and Dummy Points | |

summary.ppp | Summary of a Point Pattern Dataset | |

solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |

round.ppp | Apply Numerical Rounding to Spatial Coordinates | |

thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |

valid.ppm | Check Whether Point Process Model is Valid | |

quadrat.test.splitppp | Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts | |

scanpp | Read Point Pattern From Data File | |

vertices | Vertices of a Window | |

quad.object | Class of Quadrature Schemes | |

rho2hat | Smoothed Relative Density of Pairs of Covariate Values | |

will.expand | Test Expansion Rule | |

simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model | |

tile.areas | Compute Areas of Tiles in a Tessellation | |

volume | Volume of an Object | |

rgbim | Create Colour-Valued Pixel Image | |

vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |

Extract.psp | Extract Subset of Line Segment Pattern | |

Ginhom | Inhomogeneous Nearest Neighbour Function | |

Kcross.inhom | Inhomogeneous Cross K Function | |

anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |

anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |

area.owin | Area of a Window | |

bdist.points | Distance to Boundary of Window | |

compatible.im | Test Whether Pixel Images Are Compatible | |

convolve.im | Convolution of Pixel Images | |

crossdist | Pairwise distances | |

corners | Corners of a rectangle | |

deltametric | Delta Metric | |

crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |

dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |

flipxy | Exchange X and Y Coordinates | |

gorillas | Gorilla Nesting Sites | |

harmonise.im | Make Pixel Images Compatible | |

intersect.tess | Intersection of Two Tessellations | |

intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |

is.subset.owin | Determine Whether One Window is Contained In Another | |

matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |

methods.kppm | Methods for Cluster Point Process Models | |

pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |

nearest.raster.point | Find Pixel Nearest to a Given Point | |

pairwise.family | Pairwise Interaction Process Family | |

plot.slrm | Plot a Fitted Spatial Logistic Regression | |

psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |

rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |

reach | Interaction Distance of a Point Process | |

residuals.ppm | Residuals for Fitted Point Process Model | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

rpoint | Generate N Random Points | |

npoints | Number of Points in a Point Pattern | |

summary.im | Summarizing a Pixel Image | |

tiles | Extract List of Tiles in a Tessellation | |

No Results! |

## Last month downloads

## Details

Date | 2013-04-25 |

License | GPL (>= 2) |

URL | http://www.spatstat.org |

LazyData | true |

LazyLoad | true |

ByteCompile | true |

Packaged | 2013-04-25 07:58:13 UTC; adrian |

NeedsCompilation | yes |

Repository | CRAN |

Date/Publication | 2013-04-26 07:28:25 |

depends | base (>= 2.14.0) , deldir (>= 0.0-21) , graphics , grDevices , mgcv , R (>= 2.14.0) , stats , utils |

suggests | gpclib , gsl , locfit , maptools , RandomFields (>= 2.0) , rpanel , scatterplot3d , sm , spatial , tkrplot |

Contributors | Rolf Turner, Adrian Baddeley |

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